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A COMPARISON OF TWO METHODS FOR TESTING THE UTILITY MAXIMIZATION HYPOTHESIS WHEN QUANTITY DATA ARE MEASURED WITH ERROR

Published online by Cambridge University Press:  23 November 2005

BARRY E. JONES
Affiliation:
Binghamton University
PHILIPPE DE PERETTI
Affiliation:
Université Paris 1 Panthéon-Sorbonne

Abstract

The Generalized Axiom of Revealed Preference (GARP) can be violated because of random measurement errors in the observed quantity data. We study two tests proposed by Varian (1985) and de Peretti (2004), which test GARP within an explicit stochastic framework. Both tests compute adjusted quantity data that are compliant with GARP. We compare and contrast the two tests in theoretical terms and in an empirical application. The empirical application is based on testing a large group of monetary assets for the United States over multiple sample periods spanning 1960–1992. We found that both tests provided reasonable results and were largely consistent with each other.

Type
ARTICLES
Copyright
© 2005 Cambridge University Press

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References

Afriat S.N. 1967 The construction of utility functions from expenditure data. International Economic Review 8, 6777.Google Scholar
Anderson R.G., B.E. Jones, and T.D. Nesmith 1997 Building new monetary services indexes: concepts, data, and methods. Federal Reserve Bank of St. Louis Review 79 (1), 5382.Google Scholar
Chalfant J.A. and J.M. Alston 1988 Accounting for changes in tastes. Journal of Political Economy 96, 391410.Google Scholar
Barnett W.A. 1978 The user cost of money. Economics Letters 1, 145149. Reprinted in W.A. Barnett and A. Serletis (eds.), The Theory of Monetary Aggregation, pp. 6–10. Amsterdam: North-Holland.Google Scholar
Barnett W.A. 1980 Economic monetary aggregates: an application of index numbers and aggregation theory. Journal of Econometrics 14, 1148. Reprinted in W.A. Barnett and A. Serletis (eds.), The Theory of Monetary Aggregation, pp. 11–48. Amsterdam: North-Holland.Google Scholar
Barnett W.A. 1982 The optimal level of monetary aggregation. Journal of Money, Credit, and Banking 14, 687710. Reprinted in W.A. Barnett and A. Serletis (eds.), The Theory of Monetary Aggregation, pp. 125–149. Amsterdam: North-Holland.Google Scholar
Barnett W.A. and S. Choi 1989 A Monte Carlo study of tests of blockwise weak separability. Journal of Business and Economic Statistics 7, 363377. Reprinted in W. Barnett and J. Binner (eds.) (2004), Functional Structure and Approximation in Econometrics, pp. 257–287. Amsterdam: North Holland.Google Scholar
Barnett W.A. and A. Serletis 2000 The Theory of Monetary Aggregation. Amsterdam: North Holland.
de Peretti P. 2005a Testing the significance of the departures from utility maximization. Macro- economic Dynamics 9, 372397.Google Scholar
de Peretti P. 2005 A Multi-Step and Iterative Stochastic Nonparametric Test for Weak Separability. Unpublished manuscript, Université Paris 1 Panthéon-Sorbonne.Google Scholar
Fisher D. and A.R. Fleissig 1997 Monetary aggregation and the demand for assets. Journal of Money, Credit, and Banking 29, 458475.Google Scholar
Fleissig A.R. and G.A. Whitney 2003. A new PC-based test for Varian's weak separability conditions. Journal of Business and Economic Statistics 21, 133144.Google Scholar
Gross J. 1995 Testing data for consistency with revealed preference. Review of Economics and Statistics 77 (4), 701710.Google Scholar
Jones B.E., D.H. Dutkowsky, and T. Elger 2005 Sweep programs and optimal monetary aggregation. Journal of Banking and Finance 29, 483508.Google Scholar
Spanos A. 1999 Probability Theory and Statistical Inference. Cambridge: Cambridge University Press.
Swofford J.L. and G. Whitney 1994 A revealed preference test for weakly separable utility maximization with incomplete adjustment. Journal of Econometrics 60, 235249.Google Scholar
Thornton D. and P. Yue 1992 An extended series of divisia monetary aggregates. Federal Reserve Bank of St. Louis Review 74 (Nov./Dec.), 3546.Google Scholar
Varian H.R. 1982 The nonparametric approach to demand analysis. Econometrica 50 (4), 945973.Google Scholar
Varian H.R. 1983 Non-parametric tests of consumer behavior. Review of Economic Studies 50, 99110.Google Scholar
Varian H.R. 1985 Non-parametric analysis of optimizing behavior with measurement error. Journal of Econometrics 30, 445458.Google Scholar
Varian H. R. 1990, Goodness-of-fit in optimizing models. Journal of Econometrics 46, 125140.Google Scholar
Epstein L.G. and A. Yatchew 1985 Nonparametric hypothesis testing procedures and applications to demand analysis. Journal of Econometrics 30, 149169.Google Scholar
Zhou J.L. A.L. Tits, and C.T. Lawrence 1997 User's guide for FFSQP Version 3: a Fortran code for solving optimization programs, possibly Minimax, with general inequality constraints and linear equality constraints, generating feasible iterates. Institute for Systems Research, University of Maryland, Technical Report SRC-TR-92-107r5, College Park, MD.Google Scholar